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In this skill badge, you'll learn to evaluate retrieval systems objectively using a three-part framework (corpus, queries, and relevance judgments) that underlies every benchmark and metric in the field. You'll build intuition for core retrieval metrics (Precision, Recall@k, NDCG@k, MRR), understanding what each reveals and when to use it based on your application's failure mode. You'll also examine two real benchmarks, MS MARCO and MIRACL, to see how their design choices shape which metrics apply and what their scores can and can't tell you. The skill ends with a hands-on lab: running a full evaluation pipeline with Voyage AI and MongoDB Atlas, comparing lexical, vector, and hybrid retrieval, and interpreting results across all three. By the end, you'll be able to choose the right metric, contextualize benchmark scores for your use case, and run structured evaluations on your own data.
